Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
C4.5: programs for machine learning
C4.5: programs for machine learning
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Learning to construct knowledge bases from the World Wide Web
Artificial Intelligence - Special issue on Intelligent internet systems
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Feature Subset Selection in Text-Learning
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Multistrategy Learning for Information Extraction
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Feature Selection for Unbalanced Class Distribution and Naive Bayes
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Feature selection and feature extraction for text categorization
HLT '91 Proceedings of the workshop on Speech and Natural Language
Editorial: special issue on learning from imbalanced data sets
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Intelligent GP fusion from multiple sources for text classification
Proceedings of the 14th ACM international conference on Information and knowledge management
AdaBoost with SVM-based component classifiers
Engineering Applications of Artificial Intelligence
Imbalanced text classification: A term weighting approach
Expert Systems with Applications: An International Journal
How evolutionary algorithms are applied to statistical natural language processing
Artificial Intelligence Review
Selective costing ensemble for handling imbalanced data sets
International Journal of Hybrid Intelligent Systems
Detecting phishing e-mails by heterogeneous classification
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Refinement method of post-processing and training for improvement of automated text classification
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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The goal of the research described here is to develop a multistrategy classifier system that can be used for document categorization. The system automatically discovers classification patterns by applying several empirical learning methods to different representations for preclassified documents belonging to an imbalanced sample. The learners work in a parallel manner, where each learner carries out its own feature selection based on evolutionary techniques and then obtains a classification model. In classifying documents, the system combines the predictions of the learners by applying evolutionary techniques as well. The system relies on a modular, flexible architecture that makes no assumptions about the design of learners or the number of learners available and guarantees the independence of the thematic domain.